Numerical experiences with new truncated Newton methods in large scale unconstrained optimization

DOI10.1023/A:1008619812615zbMath0893.90154MaRDI QIDQ1363061

Massimo Roma, Stefano Lucidi

Publication date: 7 August 1997

Published in: Computational Optimization and Applications (Search for Journal in Brave)

zbMATH Keywords

Lanczos methodlarge scale unconstrained optimizationnegative curvature directiontruncated Newton methodscurvilinear linesearch

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30)

Related Items

Iterative computation of negative curvature directions in large scale optimization, A curvilinear method based on minimal-memory BFGS updates, A nonmonotone truncated Newton-Krylov method exploiting negative curvature directions, for large scale unconstrained optimization, Global convergence of nonmonotone strategies in parallel methods for block-bordered nonlinear systems, Planar conjugate gradient algorithm for large-scale unconstrained optimization. I: Theory, Planar conjugate gradient algorithm for large-scale unconstrained optimization. II: Application

Uses Software

• LANCELOT
• TNPACK
• CUTEr
• tn